Willingness to purchase Genetically Modified food: an analysis applying artificial Neural Networks

Melania Salazar-Ordóñez (), Macario Rodríguez-Entrena and D. Becerra-Alonso

No 182937, 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia from European Association of Agricultural Economists

Abstract: Findings about consumer decision-making process regarding GM food purchase remain mixed and are inconclusive. This paper offers a model which classifies willingness to purchase GM food, using data from 399 surveys in Southern Spain. Willingness to purchase has been measured using three dichotomous questions and classification, based on attitudinal, cognitive and socio-demographic factors, has been made by an artificial neural network model. The results show 74% accuracy to forecast the willingness to purchase. The highest relative contributions lie in the variables related to beliefs, especially those link to perceived risks; while the variables with the least relative contribution are age and knowledge on GMO.

Keywords: Food; Consumption/Nutrition/Food; Safety (search for similar items in EconPapers)
Pages: 6
Date: 2014-08
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Working Paper: Willingness to purchase Genetically Modified food: an analysis applying artificial Neural Networks (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:eaae14:182937

DOI: 10.22004/ag.econ.182937

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